Andy Fenton

Antagonistic coevolution accelerates molecular evolution

The Red Queen hypothesis proposes that coevolution of interacting species (such as hosts and parasites) should drive molecular evolution through continual natural selection for adaptation and counter-adaptation. Although the divergence observed at some host-resistance and parasite-infectivity genes is consistent with this, the long time periods typically required to study coevolution have so far prevented any direct empirical test. Here we show, using experimental populations of the bacterium Pseudomonas fluorescens SBW25 and its viral parasite, phage Φ2 (refs 10, 11), that the rate of molecular evolution in the phage was far higher when both bacterium and phage coevolved with each other than when phage evolved against a constant host genotype. Coevolution also resulted in far greater genetic divergence between replicate populations, which was correlated with the range of hosts that coevolved phage were able to infect. Consistent with this, the most rapidly evolving phage genes under coevolution were those involved in host infection. These results demonstrate, at both the genomic and phenotypic level, that antagonistic coevolution is a cause of rapid and divergent evolution, and is likely to be a major driver of evolutionary change within species.

Competition and mutualism among the gut helminths of a mammalian host

Most animal species are infected with multiple parasite species; however, the role of interspecific parasite interactions in influencing parasite dynamics and shaping parasite communities has been unclear. Although laboratory studies have found evidence of cross-immunity, immunosuppression and competition, analyses of hosts in the field have generally concluded that parasite communities are little more than random assemblages. Here we present evidence of consistent interspecific interactions in a natural mammalian system, revealed through the analysis of parasite intensity data collected from a free-ranging rabbit (Oryctolagus cuniculus) population, sampled monthly for a period of 23 yr. The wild rabbit plays host to a diverse gut helminth community that reflects the communities seen in other economically important domestic herbivores. These findings suggest that parasite interactions could have profound implications for the dynamics of parasite communities. The efficacy of parasite control programmes could be jeopardized if such interactions are not taken into account. In contrast, a clear understanding of such interactions may provide the basis for the development of more environmentally acceptable methods of parasite control.

Community epidemiology framework for classifying disease threats.

Ecologic and evolutionary features of multihost pathogens determine the likelihood of emerging infectious diseases.

Why infectious disease research needs community ecology

Bringing ecology to infection The tools we use to investigate infectious diseases tend to focus on specific one-host–one-pathogen relationships, but pathogens often have complex life cycles involving many hosts. Johnson et al. review how such complexity is analyzed by community ecologists. Ecologists have the investigative tools to probe cause and effect relationships that change with spatial scale in multispecies communities. These techniques are used to monitor the ways in which communities change through time and to probe the heterogeneity that characterizes individuals, species, and assemblages—all issues that are also essential for disease specialists to understand. Science, this issue 10.1126/science.1259504 BACKGROUND Despite ongoing advances in biomedicine, infectious diseases remain a major threat to human health, economic sustainability, and wildlife conservation. This is in part a result of the challenges of controlling widespread or persistent infections that involve multiple hosts, vectors, and parasite species. Moreover, many contemporary disease threats involve interactions that manifest across nested scales of biological organization, from disease progression at the within-host level to emergence and spread at the regional level. For many such infections, complete eradication is unlikely to be successful, but a broader understanding of the community in which host-parasite interactions are embedded will facilitate more effective management. Recent advances in community ecology, including findings from traits-based approaches and metacommunity theory, offer the tools and concepts to address the complexities arising from multispecies, multiscale disease threats. ADVANCES Community ecology aims to identify the factors that govern the structure, assembly, and dynamics of ecological communities. We describe how analytical and conceptual approaches from this discipline can be used to address fundamental challenges in disease research, such as (i) managing the ecological complexity of multihost-multiparasite assemblages; (ii) identifying the drivers of heterogeneities among individuals, species, and regions; and (iii) quantifying how processes link across multiple scales of biological organization to drive disease dynamics. We show how a community ecology framework can help to determine whether infection is best controlled through “defensive” approaches that reduce host suitability or through “offensive” approaches that dampen parasite spread. Examples of defensive approaches are the strategic use of wildlife diversity to reduce host and vector transmission, and taking advantage of antagonism between symbionts to suppress within-host growth and pathology. Offensive approaches include the targeted control of superspreading hosts and the reduction of human-wildlife contact rates to mitigate spillover. By identifying the importance of parasite dispersal and establishment, a community ecology framework can offer additional insights about the scale at which disease should be controlled. OUTLOOK Ongoing technological advances are rapidly overcoming previous barriers in data quality and quantity for complex, multispecies systems. The emerging synthesis of “disease community ecology” offers the tools and concepts necessary to interpret these data and use that understanding to inform the development of more effective disease control strategies in humans and wildlife. Looking forward, we emphasize the increasing importance of tight integration among surveillance, community ecology analyses, and public health implementation. Building from the rich legacy of whole-system manipulations in community ecology, we further highlight the value of large-scale experiments for understanding host-pathogen interactions and designing effective control measures. Through this blending of data, theory, and analytical approaches, we can understand how interactions between parasites within hosts, hosts within populations, and host species within ecological communities combine to drive disease dynamics, thereby providing new ways to manage emerging infections. The community ecology of disease. (A) Interactions between parasites can complicate management. Among Tsimane villagers, treatment of hookworms increases infections by Giardia lamblia. (B) Similarly, understanding how ecological communities of hosts assemble can help forecast changes in disease. Biodiversity losses can promote interactions between white-footed mice and deer ticks, leading to an increase in the risk of Lyme disease from Borrelia burgdorferi. [Credits: (A) A. Pisor, CDC, F. Dubs; (B) J. Brunner, T. Shears, NIH] Infectious diseases often emerge from interactions among multiple species and across nested levels of biological organization. Threats as diverse as Ebola virus, human malaria, and bat white-nose syndrome illustrate the need for a mechanistic understanding of the ecological interactions underlying emerging infections. We describe how recent advances in community ecology can be adopted to address contemporary challenges in disease research. These analytical tools can identify the factors governing complex assemblages of multiple hosts, parasites, and vectors, and reveal how processes link across scales from individual hosts to regions. They can also determine the drivers of heterogeneities among individuals, species, and regions to aid targeting of control strategies. We provide examples where these principles have enhanced disease management and illustrate how they can be further extended.

The nature and consequences of coinfection in humans.

Summary Objective Many fundamental patterns of coinfection (multi-species infections) are undescribed, including the relative frequency of coinfection by various pathogens, differences between single-species infections and coinfection, and the burden of coinfection on human health. We aimed to address the paucity of general knowledge on coinfection by systematically collating and analysing data from recent publications to understand the types of coinfection and their effects. Methods From an electronic search to find all publications from 2009 on coinfection and its synonyms in humans we recorded data on i) coinfecting pathogens and their effect on ii) host health and iii) intensity of infection. Results The most commonly reported coinfections differ from infections causing highest global mortality, with a notable lack of serious childhood infections in reported coinfections. We found that coinfection is generally reported to worsen human health (76% publications) and exacerbate infections (57% publications). Reported coinfections included all kinds of pathogens, but were most likely to contain bacteria. Conclusions These results suggest differences between coinfected patients and those with single infections, with coinfection having serious health effects. There is a pressing need to quantify the tendency towards negative effects and to evaluate any sampling biases in the coverage of coinfection research.

THE IMPACT OF PARASITE MANIPULATION AND PREDATOR FORAGING BEHAVIOR ON PREDATOR–PREY COMMUNITIES

Parasites are known to directly affect their hosts at both the individual and population level. However, little is known about their more subtle, indirect effects and how these may affect population and community dynamics. In particular, trophically transmitted parasites may manipulate the behavior of intermediate hosts, fundamentally altering the pattern of contact between these individuals and their predators. Here, we develop a suite of population dynamic models to explore the impact of such behavioral modifications on the dynamics and structure of the predator-prey community. We show that, although such manipulations do not directly affect the persistence of the predator and prey populations, they can greatly alter the quantitative dynamics of the community, potentially resulting in high amplitude oscillations in abundance. We show that the precise impact of host manipulation depends greatly on the predators functional response, which describes the predators foraging efficiency under changing prey availabilities. Even if the parasite is rarely observed within the prey population, such manipulations extend beyond the direct impact on the intermediate host to affect the foraging success of the predator, with profound implications for the structure and stability of the predator-prey community.

Marked seasonal variation in the wild mouse gut microbiota

Recent studies have provided an unprecedented view of the microbial communities colonizing captive mice; yet the host and environmental factors that shape the rodent gut microbiota in their natural habitat remain largely unexplored. Here, we present results from a 2-year 16 S ribosomal RNA gene sequencing-based survey of wild wood mice (Apodemus sylvaticus) in two nearby woodlands. Similar to other mammals, wild mice were colonized by 10 bacterial phyla and dominated by the Firmicutes, Bacteroidetes and Proteobacteria. Within the Firmicutes, the Lactobacillus genus was most abundant. Putative bacterial pathogens were widespread and often abundant members of the wild mouse gut microbiota. Among a suite of extrinsic (environmental) and intrinsic (host-related) factors examined, seasonal changes dominated in driving qualitative and quantitative differences in the gut microbiota. In both years examined, we observed a strong seasonal shift in gut microbial community structure, potentially due to the transition from an insect- to a seed-based diet. This involved decreased levels of Lactobacillus, and increased levels of Alistipes (Bacteroidetes phylum) and Helicobacter. We also detected more subtle but statistically significant associations between the gut microbiota and biogeography, sex, reproductive status and co-colonization with enteric nematodes. These results suggest that environmental factors have a major role in shaping temporal variations in microbial community structure within natural populations.

Predicting the impact of long-term temperature changes on the epidemiology and control of schistosomiasis: a mechanistic model.

Background Many parasites of medical and veterinary importance are transmitted by cold-blooded intermediate hosts or vectors, the abundance of which will vary with ambient temperatures, potentially altering disease prevalence. In particular, if global climate change will increase mean ambient temperature in a region endemic with a human pathogen then it is possible that the incidence of disease will similarly increase. Here we examine this possibility by using a mathematical model to explore the effects of increasing long-term mean ambient temperature on the prevalence and abundance of the parasite Schistosoma mansoni, the causative agent of schistosomiasis in humans. Principal Findings The model showed that the impact of temperature on disease prevalence and abundance is not straightforward; the mean infection burden in humans increases up to 30°C, but then crashes at 35°C, primarily due to increased mortalities of the snail intermediate host. In addition, increased temperatures changed the dynamics of disease from stable, endemic infection to unstable, epidemic cycles at 35°C. However, the prevalence of infection was largely unchanged by increasing temperatures. Temperature increases also affected the response of the model to changes in each parameter, indicating certain control strategies may become less effective with local temperature changes. At lower temperatures, the most effective single control strategy is to target the adult parasites through chemotherapy. However, as temperatures increase, targeting the snail intermediate hosts, for example through molluscicide use, becomes more effective. Conclusions These results show that S. mansoni will not respond to increased temperatures in a linear fashion, and the optimal control strategy is likely to change as temperatures change. It is only through a mechanistic approach, incorporating the combined effects of temperature on all stages of the life-cycle, that we can begin to predict the consequences of climate change on the incidence and severity of such diseases.

Stability of within-host–parasite communities in a wild mammal system

Simultaneous infection by multiple parasite species is ubiquitous in nature. Interactions among co-infecting parasites may have important consequences for disease severity, transmission and community-level responses to perturbations. However, our current view of parasite interactions in nature comes primarily from observational studies, which may be unreliable at detecting interactions. We performed a perturbation experiment in wild mice, by using an anthelminthic to suppress nematodes, and monitored the consequences for other parasite species. Overall, these parasite communities were remarkably stable to perturbation. Only one non-target parasite species responded to deworming, and this response was temporary: we found strong, but short-lived, increases in the abundance of Eimeria protozoa, which share an infection site with the dominant nematode species, suggesting local, dynamic competition. These results, providing a rare and clear experimental demonstration of interactions between helminths and co-infecting parasites in wild vertebrates, constitute an important step towards understanding the wider consequences of similar drug treatments in humans and animals.

Detecting interspecific macroparasite interactions from ecological data: patterns and process

There is great interest in the occurrence and consequences of interspecific interactions among co-infecting parasites. However, the extent to which interactions occur is unknown, because there are no validated methods for their detection. We developed a model that generated abundance data for two interacting macroparasite (e.g., helminth) species, and challenged the data with various approaches to determine whether they could detect the underlying interactions. Current approaches performed poorly - either suggesting there was no interaction when, in reality, there was a strong interaction occurring, or inferring the presence of an interaction when there was none. We suggest the novel application of a generalized linear mixed modelling (GLMM)-based approach, which we show to be more reliable than current approaches, even when infection rates of both parasites are correlated (e.g., via a shared transmission route). We suggest that the lack of clarity regarding the presence or absence of interactions in natural systems may be largely attributed to the unreliable nature of existing methods for detecting them. However, application of the GLMM approach may provide a more robust method of detection for these potentially important interspecific interactions from ecological data.